The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Search engines are common and useful tools for searching the Internet for any type of information that is web accessible. They respond to user queries by generating a list of links to documents deemed relevant to the query. Search engines are also used in proprietary websites to search for information specifically pertaining to the proprietary websites.
However, search engines perform all their work for a user only after the user has entered a query into a query field and issued the query by clicking “Search,” “Enter,” “Go” or another more or less familiar initiating input. This traditional approach is intuitive because the only time a search engine “knows” for certain what a user desires is when the user decides that the query is correct and complete by formally issuing the query. Thus, search engines do not provide help to the user while the user is formulating a query. Accordingly, search engines must “wait” to provide the search results until the user has determined that the query is complete, at which time the user explicitly issues the query to a search engine. As a logical extension, any additional information relating to the query and search results is provided after the user issues the query.
Furthermore, the manner in which the user issues subsequent queries is relatively time consuming. If the user is dissatisfied with the search results of a particular query, the user must reformulate a subsequent query and then issue that query. Again, the search engine does not provide any assistance or search results until after the subsequent query is issued.
Moreover, a number of modern search engines and/or web sites that provide access thereto are arranged with or make available to users thereof multiple verticals, which organize the presentation and availability of information and sources thereof into groups that conform to some logical arrangement. The Yahoo™ web site, available at the Uniform Resource Locator (URL) http://www.yahoo.com for instance, makes available to its users at least seven verticals. Users may access the Web (e.g., the World Wide Web, aka “WWW”) directly for running searches thereon using Yahoo's “Web” vertical. The Yahoo web site also makes available verticals labeled “Images,” “Video,” “Audio,” “Directory,” “Local,” “News,” and “Shopping.” These verticals serve as intuitively comprehensible categories with which users can more closely focus in seeking information. Similarly, the Google™ web site, available at the URL http://www.google.com, provides another familiar example. The Google web has verticals named “Web,” “Images,” “Groups,” “News,” “Froogle™”, (a shopping related vertical), “Maps,” and “Desktop.”
Although verticals available through the Yahoo, Google and similar web pages as well as more specialized web sites or web sites with a more narrow or specialized appeal allow users to focus their information gathering, a significant number of users behave as though they are unaware of these features, unsophisticated about using verticals and/or unsure of which verticals to use. Thus, many users simply avoid seeking information therewith and tend to simply perform a Web based search, e.g., a query directed across the Wed, in its entirety. At least in part, this seems to be a result of the familiarity most users have to the earlier developed and very well known Web search.
Searching the entire Web in this manner, users tend to obtain large numbers of “hits” (e.g., query results) relative to searches performed using the verticals to focus and streamline their search. However, while these users tend to obtain a relatively large number of hits using an overall Web search, all of the many results they obtain therefrom may not be fully relevant to their purposes. This places users in a position wherein they must somewhat carefully read through their search results, sometimes over multiple web pages full of hits, many of them lacking in real relevance. This practice can be tedious, time consuming, costly and prone to errors, in the sense of glossing over or skimming past a truly relevant result, which may be obscured, occluded, obfuscated and camouflaged by the plethora of their other search results, many if not most of which may be irrelevant to their true search purposes.
Sometimes this causes users to conduct one or more subsequent queries. In doing so, users may modify their query with changed or additional search terms, Boolean search additions and/or groupings such as quotation mark setoffs, conjunctive and/or disjunctive grouping symbols and the like. However, repeating queries demands time, effort and bandwidth themselves and thus bear associated costs of their own. These costs are intensified by the thoughtfulness users must apply to modify their query terms. And obviously, successive searches all make their own demands on networking and computational resources, consuming time, bandwidth, processing and memory.
One approach to addressing these issues has been for web site hosts to experiment with associating a graphical indication feature to links for one or more to their verticals, which can indicate a frequency of query results obtained that pertain to particular verticals for a given, wholly executed query. However, the indications so provided are provided upon completion of the query's execution static and are thus static. Further, some such indicators seem to ascribe an inference that hits belong in certain verticals from results obtained by searching the entire Web. Their usefulness is limited because of their static nature and/or because their accuracy in predicting relevance of the search results and/or precision in ascribing the results to a truly relevant vertical.
Based on the foregoing, there is a need for search engines to responsively and proactively suggest verticals in which a user's query may be more fruitful in terms of relevance of results and while actively assisting users with their queries as they formulate them and before the user formally issues a full and complete query.